Variable descriptions

glimpse(nri)
## Rows: 13
## Columns: 76
## $ OID_       <dbl> 47837, 47838, 63468, 63661, 65308, 65326, 69691, 69695, 697…
## $ NRI_ID     <chr> "T51001090600", "T51001980100", "T51131930100", "T511319302…
## $ STATE      <chr> "Virginia", "Virginia", "Virginia", "Virginia", "Virginia",…
## $ STATEABBRV <chr> "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA",…
## $ STATEFIPS  <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51
## $ COUNTY     <chr> "Accomack", "Accomack", "Northampton", "Northampton", "Nort…
## $ COUNTYTYPE <chr> "County", "County", "County", "County", "County", "County",…
## $ COUNTYFIPS <chr> "001", "001", "131", "131", "131", "001", "001", "001", "00…
## $ STCOFIPS   <dbl> 51001, 51001, 51131, 51131, 51131, 51001, 51001, 51001, 510…
## $ TRACT      <chr> "090600", "980100", "930100", "930200", "930300", "090300",…
## $ TRACTFIPS  <dbl> 51001090600, 51001980100, 51131930100, 51131930200, 5113193…
## $ POPULATION <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ BUILDVALUE <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ AGRIVALUE  <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ AREA       <dbl> 49.325259, 12.157470, 53.135749, 71.502115, 87.054823, 49.5…
## $ CFLD_EVNTS <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ CFLD_AFREQ <dbl> 2.743370, 2.709987, 1.202226, 1.461385, 1.292462, 2.482070,…
## $ CFLD_EXPB  <dbl> 367905008, 3772000, 110856599, 86004724, 310758713, 1348494…
## $ CFLD_EXPP  <dbl> 2434.14941, 0.00000, 814.59508, 864.14628, 2158.21462, 1490…
## $ CFLD_EXPPE <dbl> 18012705627, 0, 6028003599, 6394682493, 15970788179, 110310…
## $ CFLD_EXPT  <dbl> 18380610635, 3772000, 6138860198, 6480687217, 16281546892, …
## $ CFLD_HLRB  <dbl> 0.001493404, 0.001493404, 0.003208678, 0.003208678, 0.00320…
## $ CFLD_HLRP  <dbl> 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.011133e-07, 3.0…
## $ CFLD_HLRR  <chr> "Very Low", "Relatively High", "Relatively Low", "Relativel…
## $ DRGT_EVNTS <dbl> 91, 42, 28, 28, 28, 63, 42, 42, 42, 35, 42, 28, 42
## $ DRGT_AFREQ <dbl> 5.055556, 2.333333, 1.555556, 1.555556, 1.555556, 3.500000,…
## $ DRGT_EXPB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_EXPA  <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_EXPT  <dbl> 4848309, 0, 0, 43535471, 23747093, 0, 0, 0, 39002636, 30104…
## $ DRGT_HLRB  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRP  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
## $ DRGT_HLRA  <dbl> 0.001584889, 0.001584889, 0.003693487, 0.003693487, 0.00369…
## $ DRGT_HLRR  <chr> "Relatively Moderate", "No Rating", "No Rating", "Very High…
## $ HWAV_EVNTS <dbl> 6, 11, 7, 7, 7, 6, 6, 6, 6, 6, 6, 6, 11
## $ HWAV_AFREQ <dbl> 0.4942339, 0.5766009, 0.5766063, 0.5766063, 0.5766063, 0.49…
## $ HWAV_EXPB  <dbl> 665180718, 3772000, 595520944, 380187676, 603744461, 211227…
## $ HWAV_EXPP  <dbl> 4400.999, 0.000, 4375.999, 3819.996, 4192.997, 2334.998, 29…
## $ HWAV_EXPPE <dbl> 32567391524, 0, 32382392576, 28267973910, 31028174325, 1727…
## $ HWAV_EXPT  <dbl> 33232572241, 3772000, 32977913520, 28648161585, 31631918786…
## $ HWAV_HLRB  <dbl> 3.60888e-10, 3.60888e-10, 2.97900e-12, 2.97900e-12, 2.97900…
## $ HWAV_HLRP  <dbl> 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.901945e-07, 2.9…
## $ HWAV_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ HRCN_EVNTS <dbl> 33, 21, 28, 22, 25, 26, 21, 21, 26, 24, 25, 26, 27
## $ HRCN_AFREQ <dbl> 0.1967287, 0.2214110, 0.2239624, 0.2238779, 0.2406999, 0.22…
## $ HRCN_EXPB  <dbl> 664767958, 3769524, 595340857, 380080256, 603484965, 211227…
## $ HRCN_EXPP  <dbl> 4398.720, 0.000, 4374.935, 3818.995, 4191.471, 2334.992, 29…
## $ HRCN_EXPPE <dbl> 32550526424, 0, 32374516646, 28260566446, 31016886195, 1727…
## $ HRCN_EXPT  <dbl> 33215294382, 3769524, 32969857503, 28640646702, 31620371160…
## $ HRCN_HLRB  <dbl> 0.0006539852, 0.0006539852, 0.0011742747, 0.0011742747, 0.0…
## $ HRCN_HLRP  <dbl> 6.528385e-07, 6.528385e-07, 1.377019e-06, 1.377019e-06, 1.3…
## $ HRCN_HLRR  <chr> "Very Low", "Relatively Moderate", "Very Low", "Very Low", …
## $ RFLD_EVNTS <dbl> 13, 13, 6, 6, 6, 13, 13, 13, 13, 13, 13, 13, 13
## $ RFLD_AFREQ <dbl> 0.5909091, 0.5909091, 0.2727273, 0.2727273, 0.2727273, 0.59…
## $ RFLD_EXPB  <dbl> 202317003.4, 3429843.9, 46695447.8, 44570613.2, 149882632.4…
## $ RFLD_EXPP  <dbl> 1408.94892, 0.00000, 276.46151, 329.02285, 763.49921, 919.0…
## $ RFLD_EXPPE <dbl> 10426222026, 0, 2045815190, 2434769122, 5649894147, 6800847…
## $ RFLD_EXPA  <dbl> 3092313.16, 175094.85, 1135609.61, 2408639.57, 1343780.69, …
## $ RFLD_EXPT  <dbl> 1.063163e+10, 3.604939e+06, 2.093646e+09, 2.481748e+09, 5.8…
## $ RFLD_HLRB  <dbl> 0.0004153736, 0.0004153736, 0.0037380237, 0.0037380237, 0.0…
## $ RFLD_HLRP  <dbl> 3.925184e-06, 3.925184e-06, 1.824847e-05, 1.824847e-05, 1.8…
## $ RFLD_HLRA  <dbl> 0.001257540, 0.001257540, 0.008719085, 0.008719085, 0.00871…
## $ RFLD_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ SWND_EVNTS <dbl> 209, 161, 150, 146, 115, 162, 162, 162, 151, 155, 158, 142,…
## $ SWND_AFREQ <dbl> 6.533043, 5.062500, 4.710873, 4.582564, 3.599022, 5.076151,…
## $ SWND_EXPB  <dbl> 665181000, 3772000, 595521000, 380188000, 603745000, 211228…
## $ SWND_EXPP  <dbl> 4401, 0, 4376, 3820, 4193, 2335, 2941, 5, 6234, 4907, 2849,…
## $ SWND_EXPPE <dbl> 32567400000, 0, 32382400000, 28268000000, 31028200000, 1727…
## $ SWND_EXPA  <dbl> 14720233.70, 218489.79, 21407021.39, 43535471.38, 31048507.…
## $ SWND_EXPT  <dbl> 33247301234, 3990490, 32999328021, 28691723471, 31662993507…
## $ SWND_HLRB  <dbl> 1.648158e-05, 1.648158e-05, 1.927672e-05, 1.927672e-05, 1.9…
## $ SWND_HLRP  <dbl> 6.850051e-08, 6.850051e-08, 3.424598e-07, 3.424598e-07, 3.4…
## $ SWND_HLRA  <dbl> 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.435583e-06, 2.4…
## $ SWND_HLRR  <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ NRI_VER    <chr> "October 2020", "October 2020", "October 2020", "October 20…

Observations are census tract estimates of…

  • Population, building value, agricultural value within tract, area of tract
  • Natural hazards include: CFLD - coastal flooding, DRGT - drought, HWAV - heat wave, HRCN - hurricane, RFLD - riverine flooding, SWND - strong wind
  • Hazard measures include: EVNTS - number of events in recording period, AFREQ - annualized frequency (# events/# years in recording period)
  • Exposure measures include: EXPB - building value exposure, EXPP - population exposure, EXPE - population equivalence exposure, EXPA - agricultural value exposure
  • Historic loss ratio measures include: HLRB - historic loss ratio for building value, HLRA - historicla loss ratio for agriculture, HLRP - historical loss ratio for population, HLRR - historic loss ratio overall

Summaries

5-number summaries of (non-missing) numeric variables (remove tract identifiers)

nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>% 
  select(where(~is.numeric(.x) && !is.na(.x))) %>% 
  as.data.frame() %>% 
  stargazer(., type = "text", title = "Summary Statistics", digits = 0,
            summary.stat = c("mean", "sd", "min", "median", "max"))
## 
## Summary Statistics
## ================================================================================
## Statistic       Mean         St. Dev.       Min        Median          Max      
## --------------------------------------------------------------------------------
## POPULATION     3,504          1,942          0         3,820          6,234     
## BUILDVALUE  445,064,231    263,814,332   3,772,000  547,772,000    813,756,000  
## AGRIVALUE    19,943,077     15,182,275    31,301     21,407,021     43,535,471  
## AREA             51             27           7           53             87      
## CFLD_AFREQ       2              1            1           2              3       
## CFLD_EXPB   199,509,533    198,615,187   3,772,000  134,849,422    736,404,000  
## CFLD_EXPP      1,402           936           0         1,452          2,941     
## CFLD_EXPPE 10,371,633,091 6,922,727,785      0     10,746,133,053 21,763,400,000
## CFLD_EXPT  10,571,142,624 7,099,434,508  3,772,000 10,926,364,382 22,499,804,000
## CFLD_HLRB        0              0            0           0              0       
## CFLD_HLRP        0              0            0           0              0       
## DRGT_EVNTS       43             17          28           42             91      
## DRGT_AFREQ       2              1            2           2              5       
## DRGT_EXPA    12,767,239     16,840,163       0           0          43,535,471  
## DRGT_EXPT    12,767,239     16,840,163       0           0          43,535,471  
## DRGT_HLRA        0              0            0           0              0       
## HWAV_EVNTS       7              2            6           6              11      
## HWAV_AFREQ       1              0            0           0              1       
## HWAV_EXPB   445,064,081    263,814,292   3,772,000  547,771,848    813,755,973  
## HWAV_EXPP      3,504          1,942          0         3,820          6,234     
## HWAV_EXPPE 25,930,157,957 14,370,703,000     0     28,267,973,910 46,131,584,530
## HWAV_EXPT  26,375,222,038 14,594,282,423 3,772,000 28,648,161,585 46,679,356,378
## HWAV_HLRB        0              0            0           0              0       
## HWAV_HLRP        0              0            0           0              0       
## HRCN_EVNTS       25             3           21           25             33      
## HRCN_AFREQ       0              0            0           0              0       
## HRCN_EXPB   444,801,528    263,624,465   3,769,524  547,726,825    813,598,176  
## HRCN_EXPP      3,503          1,942          0         3,819          6,234     
## HRCN_EXPPE 25,920,530,241 14,369,165,198     0     28,260,566,446 46,129,744,254
## HRCN_EXPT  26,365,331,769 14,592,649,165 3,769,524 28,640,646,702 46,677,471,079
## HRCN_HLRB        0              0            0           0              0       
## HRCN_HLRP        0              0            0           0              0       
## RFLD_EVNTS       11             3            6           13             13      
## RFLD_AFREQ       1              0            0           1              1       
## RFLD_EXPB   106,469,319    161,601,174    301,320    51,513,125    608,324,065  
## RFLD_EXPP       605            662           0          340           2,374     
## RFLD_EXPPE 4,479,443,695  4,897,974,424      0     2,517,678,037  17,566,176,693
## RFLD_EXPA    1,935,370      1,612,333     26,074     1,964,586      5,149,665   
## RFLD_EXPT  4,587,848,385  5,052,492,472   364,660  2,574,672,609  18,174,526,832
## RFLD_HLRB        0              0            0           0              0       
## RFLD_HLRP        0              0            0           0              0       
## RFLD_HLRA        0              0            0           0              0       
## SWND_EVNTS      156             20          115         158            209      
## SWND_AFREQ       5              1            4           5              7       
## SWND_EXPB   445,064,231    263,814,332   3,772,000  547,772,000    813,756,000  
## SWND_EXPP      3,504          1,942          0         3,820          6,234     
## SWND_EXPPE 25,930,169,231 14,370,706,471     0     28,268,000,000 46,131,600,000
## SWND_EXPA    19,943,077     15,182,275    31,301     21,407,021     43,535,471  
## SWND_EXPT  26,395,176,538 14,606,328,047 3,990,490 28,691,723,471 46,718,374,636
## SWND_HLRB        0              0            0           0              0       
## SWND_HLRP        0              0            0           0              0       
## SWND_HLRA        0              0            0           0              0       
## --------------------------------------------------------------------------------

Summaries of (non-missing) character variables (remove tract identifiers)

nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>% 
  select(where (~is.character(.x))) %>% map(tabyl)
## $COUNTY
##      .x[[i]]  n   percent
##     Accomack 10 0.7692308
##  Northampton  3 0.2307692
## 
## $CFLD_HLRR
##              .x[[i]] n    percent
##      Relatively High 1 0.07692308
##       Relatively Low 4 0.30769231
##  Relatively Moderate 1 0.07692308
##             Very Low 7 0.53846154
## 
## $DRGT_HLRR
##              .x[[i]] n   percent
##            No Rating 7 0.5384615
##  Relatively Moderate 4 0.3076923
##            Very High 2 0.1538462
## 
## $HWAV_HLRR
##   .x[[i]]  n percent
##  Very Low 13       1
## 
## $HRCN_HLRR
##              .x[[i]]  n    percent
##       Relatively Low  1 0.07692308
##  Relatively Moderate  1 0.07692308
##             Very Low 11 0.84615385
## 
## $RFLD_HLRR
##   .x[[i]]  n percent
##  Very Low 13       1
## 
## $SWND_HLRR
##   .x[[i]]  n percent
##  Very Low 13       1

Visual distribution

Via a grouped series of histograms

Tract assets

nri %>% select(TRACTFIPS:AREA) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  geom_histogram() + 
  facet_wrap(~measure, scales = "free")

Tract hazards: Coastal Flooding

# Tract hazards: CFLD
nri %>% select(contains("CFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Drought

nri %>% select(contains("DRGT"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Heat Wave

nri %>% select(contains("HWAV"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Hurricane

nri %>% select(contains("HRCN"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Riverine Flooding

nri %>% select(contains("RFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Tract hazards: Strong Wind

nri %>% select(contains("SWND"), TRACTFIPS) %>% select(-contains("HLRR")) %>% 
  pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>% 
  ggplot(aes(x = value, fill = measure)) + 
  geom_histogram() + 
  scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
  facet_wrap(~measure, scales = "free")

Maps

Coastal Flooding

# CFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$CFLD_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(CFLD_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$CFLD_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$CFLD_AFREQ, 
            title = "Coastal Flooding-#/year", opacity = 0.7)

Droughts

# DRGT
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$DRGT_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(DRGT_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$DRGT_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$DRGT_AFREQ, 
            title = "Drought-#/year", opacity = 0.7)

Heat Wave

# HWAV
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HWAV_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(HWAV_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$HWAV_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$HWAV_AFREQ, 
            title = "Heat Wave-#/year", opacity = 0.7)

Hurricane

# HRCN
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$HRCN_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(HRCN_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$HRCN_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$HRCN_AFREQ, 
            title = "Hurricane-#/year", opacity = 0.7)

Riverine Flooding

# RFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$RFLD_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(RFLD_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$RFLD_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$RFLD_AFREQ, 
            title = "Riverine Flooding-#/year", opacity = 0.7)

Strong Wind

# SWND
pal <- colorNumeric("plasma", reverse = TRUE, domain = eastern_nri$SWND_AFREQ) # viridis

leaflet() %>% 
  addProviderTiles("CartoDB.Positron") %>% 
  addPolygons(data = eastern_nri,
              fillColor = ~pal(SWND_AFREQ),
              weight = 1,
              opacity = 1,
              color = "white", 
              fillOpacity = 0.6,
              highlight = highlightOptions(
                weight = 2,
                fillOpacity = 0.8,
                bringToFront = T
              ),
              popup = paste0("Tract Number: ", eastern_nri$NAME, "<br>",
                             "Ann. Freq.: ", round(eastern_nri$SWND_AFREQ, 2))
  ) %>% 
  addLegend("bottomright", pal = pal, values = eastern_nri$SWND_AFREQ, 
            title = "Strong Wind-#/year", opacity = 0.7)

Nota Bene

  • Several hazard rates are dominated by regional measures, with little variation identified within the region.